Abstract

This study explores damage identification and load estimation in composite structures using Artificial Neural Networks (ANNs) and its application to a composite test box. The test box contains a debond between its spar and skin. The box was loaded and strains were captured at several locations using Fiber Bragg Grating (FBG) sensors as well as strain gages. The difference in strains between healthy and unhealthy box is indicative of the presence of damage, as well as its extent and the loads seen by the box. ANNs were trained using data generated from finite element (FE) analyses of the test box. These trained ANNs were then used to estimate the applied load, debond size and location on the box. Damage and load predicted by the ANNs were verified using tests on the box.